Do you think Hollywood has lost touch with American values? Do you think Hollywood has lost touch with American values? The contentious presidential campaign was filled with accusations of elitism and bias by the media -- from the news to entertainment. Many supporters of Donald J. Trump saw his victory as a repudiation of the so-called liberal elite. So as 2017 begins, we ask: Is Hollywood representing all Americans? Are Hollywood values out of sync with American values? It's the start of a conversation we'll have all year with Hollywood's creators, consumers and observers. Most of all, we want to hear from you. Is Hollywood out of touch with your America? Here's what our critics and writers have to say: KENNETH TURAN on potent Hollywood visions that helped elect Trump TV's affluent bubble: MARY McNAMARA on Hollywood's reluctance to deal with class issues Fear of the powerful woman: JUSTIN CHANG on working women and men still behaving badly Realistic or cliche?: JEFFREY FLEISHMAN on ...

If you've stumbled upon this article, you may already be in this position. However, what's more likely is that this is going to become your situation in near future, and learning from someone else's experience is now needed to prepare. While there's a plethora of theory around business applications for data analytics; there is a significant lack of practical, real-life experience to draw on. This is largely due to the fact that adoption of these technologies, for many industries, is new and the results of pilots are just coming to light now. Machine learning technologies are successfully used in predictive and recommendation services.

The contentious presidential campaign was filled with accusations of elitism and bias by the media -- from the news to entertainment. Many supporters of Donald J. Trump saw his victory as a repudiation of the so-called liberal elite. So as 2017 begins, we ask: Is Hollywood representing all Americans? Are Hollywood values out of sync with American values? It's the start of a conversation we'll have all year with Hollywood's creators, consumers and observers. Most of all, we want to hear from you . Is Hollywood out of touch with your America? Here's what our critics and writers have to say: KENNETH TURAN on potent Hollywood visions that helped elect Trump TV's affluent bubble: MARY McNAMARA on Hollywood's reluctance to deal with class issues Fear of the powerful woman: JUSTIN CHANG on working women and men still behaving badly Realistic or cliche?: JEFFREY FLEISHMAN on film's working class men and women Building distrust: LORRAINE ALI on destructive TV portrayals of Muslims and how TV ...

Underground mining poses a number of threats including fires, methane outbreaks or seismic tremors and bumps. An automatic system for predicting and alerting against such dangerous events is of utmost importance – and also a great challenge for data scientists and their machine learning models. This was the inspiration for the organizers of AAIA'16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Coal Mines. Our solutions topped the final leaderboard by taking the first two places. In this post, we present the competition and describe our winning approach.

Food and agribusiness comprise a $5 trillion industry that accounts for 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse-gas emissions. This massive industry does not change easily, but change – transformative innovation – is precisely what's needed. We collected some examples of artificial intelligence techniques that can help farmers to save thousands of dollars. Three years ago Belarusian startup OneSoil was created. It's an online service to monitor the status of sown areas, which can increase productivity and save resources with the help of artificial intelligence.

Machine learning and data mining are research areas of computer science whose quick development is due to the advances in data analysis research, growth in the database industry and the resulting world construction market needs for methods that are capable of extracting valuable knowledge from large data stores. Here are some of the examples of machine learning being applied in the construction industry. It's important to note that machine learning techniques apply mostly on a business side, less so in the actual construction. At the same time, the construction industry is currently experiencing explosive growth in its capability to generate and collect data. Advances in data storage technology, such as faster, higher capacity, and less expensive storage devices, better database management systems, and data-warehousing technology, have allowed the transformation of an enormous amount of data into computerized database systems. These data, however, have no use until they are processed and interpreted.

We propose a method for recovering the structure of a sparse undirected graphical model when very few samples are available. The method decides about the presence or absence of bonds between pairs of variable by considering one pair at a time and using a closed form formula, analytically derived by calculating the posterior probability for every possible model explaining a two body system using Jeffreys prior. The approach does not rely on the optimization of any cost functions and consequently is much faster than existing algorithms. Despite this time and computational advantage, numerical results show that for several sparse topologies the algorithm is comparable to the best existing algorithms, and is more accurate in the presence of hidden variables. We apply this approach to the analysis of US stock market data and to neural data, in order to show its efficiency in recovering robust statistical dependencies in real data with non-stationary correlations in time and/or space.

Along with an entire generation of comic book fans, Chao Wang grew up following the exploits of Wolverine, a.k.a Now an assistant professor of chemistry at University of Califormia, Riverside, Wang recently paid tribute to his childhood hero, in a chemical engineering sort of way. Wang and a group of collaborators have developed a transparent and stretchable material that could give future robots the ability to heal rapidly, similar to Wolverine's handy superpower. According to the research team, the space-age material could power artificial muscles that mend themselves after injury or normal wear-and-tear. Researchers say that the artificial skin represents the first time scientists have created an ionic conductor that's stretchable, transparent and able to heal itself.

Machine learning and artificial intelligence are all the rage today in venture capital circles. We've seen spectacular exits in the past few years, from Google absorbing Deepmind in 2014 for $500 million, to Twitter buying TellApart in 2015 for $533 million, and Intel swallowing Nervana in 2016 for $400 million. But these were all IT plays. Berkeley-based Lygos is engineering and designing microbes that convert low-cost sugar into high-value, specialty chemicals. Ultimately, the ability to design and optimize microbes, or program them, is becoming faster and cheaper than ever before.

This year, we kicked things off by telling you how deadly and difficult space is to explore. It can kill you with radiation, giant flying space rocks, and regular old time. And those are just a few of its weapons. But while space is a pretty dangerous place, it's also incredibly inspirational. If you take science fiction as your model--which we often do--people are at their best when faced with a seemingly insurmountable challenge.